1. Field of the Invention
The field of the invention is data processing, or, more specifically, methods, apparatus, and products for graphical retail item identification.
2. Description of Related Art
The development of the EDVAC computer system of 1948 is often cited as the beginning of the computer era. Since that time, computer systems have evolved into extremely complicated devices. Today's computers are much more sophisticated than early systems such as the EDVAC. Computer systems typically include a combination of hardware and software components, application programs, operating systems, processors, buses, memory, input/output devices, and so on. As advances in semiconductor processing and computer architecture push the performance of the computer higher and higher, more sophisticated computer software has evolved to take advantage of the higher performance of the hardware, resulting in computer systems today that are much more powerful than just a few years ago.
Computer systems of various implementations today are relied on greatly by many industries. One such industry that relies on computer systems is the retail industry. In typical, high item count retail establishments, items that are to be purchased have barcodes printed on the packaging where a scanner in a checkout lane decodes the label into a number. These scanners are self contained units that are designed to only decode barcodes meeting a defined set of standards. The speed at which the scanners can actually recognize a barcode varies greatly. Some scanners use reflections of moving laser beams off a barcode to recognize and decode the barcode, while others capture a picture of the barcode, and image processing software within the scanner processes the barcode to find a matching valid barcode pattern.
In most scanning situations, the barcode must be positioned in a certain orientation for the scanner to accurately detect and decode the barcode. What would be far more desirable would a system that would recognize the item based on the item's appearance and not on a barcode. Image identification of this type, however, is expensive to implement due to the amount of processing power required for such object recognition to occur in a timely manner. A typical grocery store, for example, contains approximately 30,000 individual items, and recognizing one item from the 30,000 requires a vast amount of computing power. Moreover, in order for item recognition to be used efficiently, items must be recognized in 100-200 milliseconds or less.
There are numerous algorithms for image recognition. Many of these algorithms lend themselves well to parallel processing techniques where various parameters of a single image are processed by many processors simultaneously to carry out a complete image processing method. This can be far faster than a single processor performing these steps sequentially.
Consider as an example, a high volume grocery store or mass merchandise store. These stores have approximately 30-80 networked POS terminals within the store. Each of these POS terminals may include very high performance processors, some with dual core processors for example. Many of these 30-80 POS terminals area also typically idle or under a very low processor load. In addition, even when a terminal is under some load, the load is typically very low compared to the processor's maximum capability. This is so, because POS terminals, by their nature, are typically I/O bound, that is, waiting for the operator, waiting for a hard drive, waiting for the server, and so on. The processor of a POS terminal typically does very few, if any, resource intensive tasks. In addition, most networked POS terminals are interconnected with in a high speed local area network, such as an Ethernet or Fibre Channel network, capable of moving large amounts of data between the terminals very quickly. Readers of skill in the art will recognize that what is needed is a graphical method of retail item identification that is carried out by such networked POS terminals where the available computer processing resources of the POS terminals may be harnessed for image processing.